code: def get_all_loss_operators():
      """Gets all Neural Network loss operators registered with MXNet.
  
      Returns
      -------
      {"operator_name": {"has_backward", "nd_op_handle", "params"}}
      """
      loss_ops = {
          "smooth_l1",
          "CTCLoss",
          "ctc_loss",
          "MakeLoss",
          "softmax_cross_entropy",
      }
  
      # Get all mxnet operators
      mx_operators = _get_all_mxnet_operators()
  
      # Filter for NN Loss operators
      loss_mx_operators = {}
      for op_name, _ in mx_operators.items():
          if op_name in loss_ops:
              loss_mx_operators[op_name] = mx_operators[op_name]
      return loss_mx_operators
  
imports: from operator import itemgetter
  from mxnet import runtime
  import mxnet
  from benchmark.opperf.rules.default_params import DEFAULTS_INPUTS, DEFAULTS_INPUTS_LARGE_TENSOR, MX_OP_MODULE
label_desc: Use image node_id 20 for calling a global function with example usage: get_all_loss_operators() and returns: loss_mx_operators